- Rewrite TECHNICAL_REPORT_v1.1.md to ACL Long Paper format: Abstract,
Introduction, Related Work, Dataset, AL Framework, Experiments, Results,
Analysis, Conclusion, Limitations, Ethics Statement, References, Appendices
- Add Phase 0 gold evaluation set (500 random sentences, 250 dev + 250 test)
to PLAN_v1.1 and technical report, following AL evaluation best practices
- Add BKTreebank (Nguyen 2018) to Related Work with treebank comparison table
- Add comprehensive Limitations section (8 items) and Ethics Statement
- Add 7 new citations: VLSP 2013, VnCoreNLP, Zhang 2022 survey, Bouma 2017,
Farquhar 2021, Luth 2023, Marcus 1993, BKTreebank
- Add AL Cycle 1 report, gold annotations, references, and research materials
- Update annotation tooling and regenerate dataset with fix pipeline
Regenerate UDD-WS v1.1 dataset and update annotation tooling
- Add src/al_score_ws.py: CRF marginal uncertainty scoring on 20K dev+test
sentences (Word F1 baseline: 0.9848, top 500 selected for annotation)
- Add al_cycle0_ranked.tsv (all 20K ranked) and al_cycle0_top500.tsv
- Update PLAN_v1.1.md with baseline results and AL cycle status
- Move udtools from src/ to tools/, update CLAUDE.md references
- Move references/ and active_learning/ into research/
- Convert sentence selection guideline to directory structure
- Add word segmentation annotation guideline under guidelines/
Add v1.1 word segmentation dataset, annotation guidelines, and research references
- Add 100K-sentence word segmentation dataset in BIO format (udd-ws-v1.1-{train,dev,test})
- Add raw sentence files for 5 domains (ws_sentences_*.txt)
- Add word segmentation annotation guideline and segmentation evaluation report
- Add technical report v1.0 and review documents
- Add active learning research references and Vietnamese UD annotation references
- Add sentence selection guidelines
- Move scripts/ to src/ (udtools, gpu_stats, run_conversion, etc.)
- Track large training files with Git LFS
Add word segmentation dataset pipeline and technical report v1.1
- Add src/fetch_ws_sentences.py: fetches 100K sentences (20K × 5 domains)
from HuggingFace datasets with domain-specific quality filters
- Add src/build_ws_dataset.py: converts sentences to BIO format (VLSP 2013
compatible) with stratified 80/10/10 train/dev/test splits
- Add src/ws_statistics.py: computes dataset statistics and converts BIO
files to CoNLL-U format
- Update CLAUDE.md with WS dataset pipeline documentation
- Add TECHNICAL_REPORT_1.1.md: documents udd-ws-v1.1 dataset and proposes
active learning framework for gold-standard Vietnamese UD annotation
with solo annotator setting and task-specific AL strategies for WS,
POS tagging, and dependency parsing
Add fetch scripts for news (UVN-1) and Wikipedia (UVW-2026) domains.
Increase sentence targets to 8K per domain for legal and books.
Add build_dataset.py to combine all domains with sent_id prefixes
and create stratified train/dev/test splits. Update convert_to_ud.py
to support domain-specific sent_ids and upload_to_hf.py for multi-split
upload with domain field.
Add batch processing and run script for GPU optimization
- Update convert_to_ud.py with batch processing and model pre-loading
- Add gpu_stats.py for monitoring GPU utilization as table
- Add run_conversion.sh to save results to timestamped folders
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
